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Record W2789389748 · doi:10.1126/science.aar7186

The threshold for conscious report: Signal loss and response bias in visual and frontal cortex

2018· article· en· W2789389748 on OpenAlexfundno aff
Bram van Vugt, Bruno Dagnino, Devavrat Vartak, Houman Safaai, Stefano Panzeri, Stanislas Dehaene, Pieter R. Roelfsema

Bibliographic record

VenueScience · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsnot available
FundersFP7 People: Marie-Curie ActionsEuropean CommissionFondation BertarelliHorizon 2020 Framework ProgrammeFP7 Ideas: European Research CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekCanadian Institute for Advanced Research
KeywordsVisual cortexNeurosciencePsychologyConsciousnessAudiologySIGNAL (programming language)Frontal cortexCognitive psychologyCortex (anatomy)MedicineComputer science

Abstract

fetched live from OpenAlex

Why are some visual stimuli consciously detected, whereas others remain subliminal? We investigated the fate of weak visual stimuli in the visual and frontal cortex of awake monkeys trained to report stimulus presence. Reported stimuli were associated with strong sustained activity in the frontal cortex, and frontal activity was weaker and quickly decayed for unreported stimuli. Information about weak stimuli could be lost at successive stages en route from the visual to the frontal cortex, and these propagation failures were confirmed through microstimulation of area V1. Fluctuations in response bias and sensitivity during perception of identical stimuli were traced back to prestimulus brain-state markers. A model in which stimuli become consciously reportable when they elicit a nonlinear ignition process in higher cortical areas explained our results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.317
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations428
Published2018
Admission routes1
Has abstractyes

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